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Gramene (http://www.gramene.org), a knowledgebase founded on comparative functional analyses of genomic and pathway data for model plants and major crops, supports agricultural researchers worldwide. The resource is committed to open access and reproducible science based on the FAIR data principles. Since the last NAR update, we made nine releases; doubled the genome portal's content; expanded curated genes, pathways and expression sets; and implemented the Domain Informational Vocabulary Extraction (DIVE) algorithm for extracting gene function information from publications. The current release, #63 (October 2020), hosts 93 reference genomes—over 3.9 million genes in 122 947 families with orthologous and paralogous classifications. Plant Reactome portrays pathway networks using a combination of manual biocuration in rice (320 reference pathways) and orthology-based projections to 106 species. The Reactome platform facilitates comparison between reference and projected pathways, gene expression analyses and overlays of gene–gene interactions. Gramene integrates ontology-based protein structure–function annotation; information on genetic, epigenetic, expression, and phenotypic diversity; and gene functional annotations extracted from plant-focused journals using DIVE. We train plant researchers in biocuration of genes and pathways; host curated maize gene structures as tracks in the maize genome browser; and integrate curated rice genes and pathways in the Plant Reactome.

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of interfaces to genomic data across the tree of life, including reference genome sequence, gene models, transcriptional data, genetic variation and comparative analysis. Data may be accessed via our website, online tools platform and programmatic interfaces, with updates made four times per year (in synchrony with Ensembl). Here, we provide an overview of Ensembl Genomes, with a focus on recent developments. These include the continued growth, more robust and reproducible sets of orthologues and paralogues, and enriched views of gene expression and gene function in plants. Finally, we report on our continued deeper integration with the Ensembl project, which forms a key part of our future strategy for dealing with the increasing quantity of available genome-scale data across the tree of life.

Natural populations are characterized by abundant genetic diversity driven by a range of different types of mutation. The tractability of sequencing complete genomes has allowed new insights into the variable composition of genomes, summarized as a species pan-genome. These analyses demonstrate that many genes are absent from the first reference genomes, whose analysis dominated the initial years of the genomic era. Our field now turns towards understanding the functional consequence of these highly variable genomes. Here, we analyzed weighted gene co-expression networks from leaf transcriptome data for drought response in the purple false brome Brachypodium distachyon and the differential expression of genes putatively involved in adaptation to this stressor. We specifically asked whether genes with variable “occupancy” in the pan-genome – genes which are either present in all studied genotypes or missing in some genotypes – show different distributions among co-expression modules. Co-expression analysis united genes expressed in drought-stressed plants into nine modules covering 72 hub genes (87 hub isoforms), and genes expressed under controlled water conditions into 13 modules, covering 190 hub genes (251 hub isoforms). We find that low occupancy pan-genes are under-represented among several modules, while other modules are over-enriched for low-occupancy pan-genes. We also provide new insight into the regulation of drought response in B. distachyon, specifically identifying one module with an apparent role in primary metabolism that is strongly responsive to drought. Our work shows the power of integrating pan-genomic analysis with transcriptomic data using factorial experiments to understand the functional genomics of environmental response.

Unraveling the evolution of plant polyploids is a challenge when their diploid progenitor species are extinct or unknown or when their progenitor genome sequences are unavailable. The subgenome identification methods cannot adequately retrieve the homeologous genomes that are present in the allopolyploids if they do not take into account the potential existence of unknown progenitors. We addressed this challenge in the widely distributed dysploid grass genus Brachypodium, which is a model genus for temperate cereals and biofuel grasses. We used a transcriptome-based phylogeny and newly designed subgenome detection algorithms coupled with a comparative chromosome barcoding analysis. Our phylogenomic subgenome detection pipeline was validated in Triticum allopolyploids, which have known progenitor genomes, and was used to infer the identities of three extant and four ‘ghost’ subgenomes in six Brachypodium polyploids (B. mexicanum, B. boissieri, B. retusum, B. phoenicoides, B. rupestre and B. hybridum), of which five contain undescribed homeologous subgenomes. The existence of the seven Brachypodium progenitor genomes in the polyploids was confirmed by their karyotypic barcode profiles. Our results demonstrate that our subgenome detection method is able to uncover the ancestral genomic components of both allo- and autopolyploids.

Ii.Summary/AbstractThe annotation of repetitive sequences within plant genomes can help in the interpretation of observed phenotypes. Moreover, repeat masking is required for tasks such as whole-genome alignment, promoter analysis or pangenome exploration. While homology-based annotation methods are computationally expensive, k-mer strategies for masking are orders of magnitude faster. Here we benchmark a two-step approach, where repeats are first called by k-mer counting and then annotated by comparison to curated libraries. This hybrid protocol was tested on 20 plant genomes from Ensembl, using the kmer-based Repeat Detector (Red) and two repeat libraries (REdat and nrTEplants, curated for this work). We obtained repeated genome fractions that match those reported in the literature, but with shorter repeated elements than those produced with conventional annotators. Inspection of masked regions overlapping genes revealed no preference for specific protein domains. Half of Red masked sequences can be successfully classified with nrTEplants, with the complete protocol taking less than 2h on a desktop Linux box. The repeat library and the scripts to mask and annotate plant genomes can be obtained at https://github.com/Ensembl/plant-scripts.

17 Pags.- 3 Tabls.- 7 Figs. © Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence., The identification of functional elements encoded in plant genomes is necessary to understand gene regulation. Although much attention has been paid to model species like Arabidopsis (Arabidopsis thaliana), little is known about regulatory motifs in other plants. Here, we describe a bottom-up approach for de novo motif discovery using peach (Prunus persica) as an example. These predictions require pre-computed gene clusters grouped by their expression similarity. After optimizing the boundaries of proximal promoter regions, two motif discovery algorithms from RSAT::Plants (http://plants.rsat.eu) were tested (oligo and dyad analysis). Overall, 18 out of 45 co-expressed modules were enriched in motifs typical of well-known transcription factor (TF) families (bHLH, bZip, BZR, CAMTA, DOF, E2FE, AP2-ERF, Myb-like, NAC, TCP, and WRKY) and a few uncharacterized motifs. Our results indicate that small modules and promoter window of [–500 bp, +200 bp] relative to the transcription start site (TSS) maximize the number of motifs found and reduce low-complexity signals in peach. The distribution of discovered regulatory sites was unbalanced, as they accumulated around the TSS. This approach was benchmarked by testing two different expression-based clustering algorithms (network-based and hierarchical) and, as control, genes grouped for harboring ChIPseq peaks of the same Arabidopsis TF. The method was also verified on maize (Zea mays), a species with a large genome. In summary, this article presents a glimpse of the peach regulatory components at genome scale and provides a general protocol that can be applied to other species. A Docker software container is released to facilitate the reproduction of these analyses., This work was partly funded by the Spanish Ministry of Economy and Competitiveness grants AGL2014-52063R, AGL2017-83358-R (MCIU/AEI/FEDER/UE); and the Government of Aragón with grants A44, A08_17R and A09_17R, which were co-financed with FEDER funds. N.K. was funded by project AGL2014-52063R, two months of Erasmus plus traineeship at Aix-Marseille University (AMU; Lab.Technological Advances for Genomics and Clinics (TAGC)) and at present a PhD contract awarded by the Government of Aragón.

16 Pags.- 8 Figs. This article is licensed under a Creative Commons Attribution 4.0 International License., Our understanding of polyploid genome evolution is constrained because we cannot know the exact founders of a particular polyploid. To differentiate between founder effects and post polyploidization evolution, we use a pan-genomic approach to study the allotetraploid Brachypodium hybridum and its diploid progenitors. Comparative analysis suggests that most B. hybridum whole gene presence/absence variation is part of the standing variation in its diploid progenitors. Analysis of nuclear single nucleotide variants, plastomes and k-mers associated with retrotransposons reveals two independent origins for B. hybridum, ~1.4 and ~0.14 million years ago. Examination of gene expression in the younger B. hybridum lineage reveals no bias in overall subgenome expression. Our results are consistent with a gradual accumulation of genomic changes after polyploidization and a lack of subgenome expression dominance. Significantly, if we did not use a pan-genomic approach, we would grossly overestimate the number of genomic changes attributable to post polyploidization evolution., The work conducted by the US DOE Joint Genome Institute is supported by the Office of Science of the US Department of Energy under Contract no. DE-AC02-05CH11231 and User Agreement No. FP00006675 between the University of Zaragoza (User) and the DOE (Community Science Program 503504 proposal); S.J. was supported by the DOE Office of Science Graduate Student Research Program; P.C., B.C.-M., A.D.P., and R.S. were supported by a Spanish Ministry of Economy and Competitiveness grant CGL2016-79790-P; P.C., A.D.P., and R.S. were supported by a Bioflora A01-17 grant co-funded by the Spanish Aragon Government and the European Social Fund. R.H., E.W., and J.L. were supported by the National Science Centre Poland (grants DEC-2012/04/A/NZ3/00572 and DEC-2014/14/M/NZ2/00519). J.H.D. and C.N. were supported by Leverhulme Trust (grant no. 10754). A.C.E. and A.D. were supported by the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013)/ERC grant agreement no [GA335691 “Effectomics”], the Austrian Science Fund (FWF): [P27429-B22, P27818-B22, I 3033-B22], and the Austrian Academy of Science (OEAW).

Gene regulatory regions contain short and degenerated DNA sites recognized by transcription factors (TFs). When such regions harbor SNPs, the DNA motifs where TFs bind may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in GWAS studies. In this study, we describe the application of the programs Var-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Var-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted TF affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Vart-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis.

22 Pags.- 3 Tabls.- 7 Figs. Creative Commons License Attribution 4.0 International (CC BY 4.0)., The massive accumulation of genome-sequences in public databases promoted the proliferation of genome-level phylogenetic analyses in many areas of biological research. However, due to diverse evolutionary and genetic processes, many loci have undesirable properties for phylogenetic reconstruction. These, if undetected, can result in erroneous or biased estimates, particularly when estimating species trees from concatenated datasets. To deal with these problems, we developed GET_PHYLOMARKERS, a pipeline designed to identify high-quality markers to estimate robust genome phylogenies from the orthologous clusters, or the pan-genome matrix (PGM), computed by GET_HOMOLOGUES. In the first context, a set of sequential filters are applied to exclude recombinant alignments and those producing anomalous or poorly resolved trees. Multiple sequence alignments and maximum likelihood (ML) phylogenies are computed in parallel on multi-core computers. A ML species tree is estimated from the concatenated set of top-ranking alignments at the DNA or protein levels, using either FastTree or IQ-TREE (IQT). The latter is used by default due to its superior performance revealed in an extensive benchmark analysis. In addition, parsimony and ML phylogenies can be estimated from the PGM. We demonstrate the practical utility of the software by analyzing 170 Stenotrophomonas genome sequences available in RefSeq and 10 new complete genomes of Mexican environmental S. maltophilia complex (Smc) isolates reported herein. A combination of core-genome and PGM analyses was used to revise the molecular systematics of the genus. An unsupervised learning approach that uses a goodness of clustering statistic identified 20 groups within the Smc at a core-genome average nucleotide identity (cgANIb) of 95.9% that are perfectly consistent with strongly supported clades on the core- and pan-genome trees. In addition, we identified 16 misclassified RefSeq genome sequences, 14 of them labeled as S. maltophilia, demonstrating the broad utility of the software for phylogenomics and geno-taxonomic studies. The code, a detailed manual and tutorials are freely available for Linux/UNIX servers under the GNU GPLv3 license at https://github.com/vinuesa/get_phylomarkers. A docker image bundling GET_PHYLOMARKERS with GET_HOMOLOGUES is available at https://hub.docker.com/r/csicunam/get_homologues/, which can be easily run on any platform., We gratefully acknowledge the funding provided by DGAPA/PAPIIT-UNAM (grants IN201806-2, IN211814 and IN206318) and CONACyT-México (grants P1-60071, 179133 and FC-2105-2-879) to PV, as well as the Fundación ARAID, Consejo Superior de Investigaciones Científicas (grant 200720I038 and Spanish MINECO (AGL2013-48756-R) to BC-M.

13 Pags.- 6 Figs. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder, While prokaryotic pan-genomes have been shown to contain many more genes than any individual organism, the prevalence and functional significance of differentially present genes in eukaryotes remains poorly understood. Whole-genome de novo assembly and annotation of 54 lines of the grass Brachypodium distachyon yield a pan-genome containing nearly twice the number of genes found in any individual genome. Genes present in all lines are enriched for essential biological functions, while genes present in only some lines are enriched for conditionally beneficial functions (e.g., defense and development), display faster evolutionary rates, lie closer to transposable elements and are less likely to be syntenic with orthologous genes in other grasses. Our data suggest that differentially present genes contribute substantially to phenotypic variation within a eukaryote species, these genes have a major influence in population genetics, and transposable elements play a key role in pan-genome evolution., The work conducted by the US DOE Joint Genome Institute is supported by the Office of Science of the US Department of Energy under Contract no. DE-AC02-05CH11231. D.P. W. and R.A. were funded in part by the National Science Foundation (grant no. IOS–1258126), and the Great Lakes Bioenergy Research Center (Department of Energy Biological and Environmental Research Office of Science grant no. DE– FCO2–07ER64494). TEJ and DLDM were supported by NSF PGRP grant IOS-0922457. P.C. and B.C.M. were funded by Spanish MINECO (CGL2012-39953-C02-01 and CGL2016-79790-P). B.C.M. was partially funded by DGA—Obra Social La Caixa (grant number GA-LC-059-2011) and Spanish MINECO (AGL2013-48756-R, CSIC13-4E-2490). PC was partially funded by Spanish Aragon Government-European Social Fund (Bioflora).

17 pags.- 7 Figs.- 1 Tabl. © The Authors 2017. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., The increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging. We describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare, and infer complex metabolic pathways in large “omic” datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome_Pfam_score. To demonstrate its use, we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways, and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H΄), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used both to build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, receiver operator characteristic plots, and the area under the curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC = 0.985) hard-to-culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones, and metagenomic environments such as hydrothermal vents, or deep-sea sediment. Our benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and can be used to efficiently classify large genomic and metagenomic datasets, including uncultivated/unexplored taxa., Valerie De Anda is a doctoral student from Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México (UNAM), and received fellowship 356 832 from Consejo Nacional de Ciencia y Tecnología (CONACYT). This research was also supported by funding from World Wildlife Fund (WWF)-Alianza Carlos Slim, Sep-Ciencia Básica Conacyt grant 238 245 to both Valeria Souza and Luis Enrique Eguiarte and Spanish MINECO grant CSIC13–4E-2490. Bruno Contreras Moreira was funded by Fundación ARAID. The sabbatical leaves of Luis Enrique Eguiarte and Valeria Souza at the University of Minnesota were supported by scholarships from Programa de Apoyos para la Superación del Personal Académico de la UNAM (PASPA), Dirección General de Asuntos del Personal Académico (DGAPA), UNAM.

10 Págs., 4 Figs., 2 Tabls., 1 add. file (17 Págs.) with 8 Figs., 2 Tabls. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited., Background - Intrinsically disordered proteins, found in all living organisms, are essential for basic cellular functions and complement the function of ordered proteins. It has been shown that protein disorder is linked to the G + C content of the genome. Furthermore, rec ent investigations have suggested that the evolutionary dynamics of the plant nucleus adds disordered segments to open reading frames alike, and these segments are not necessarily conserved among orthologous genes. Results - In the present work the distribution of intrinsically disordered proteins along the chromosomes of several representative plants was analyzed. The reported results support a non-random distribution of disordered proteins along the chromosomes of Arabidopsis thaliana and Oryza sativa, two model eudicot and monocot plant species, respectively. In fact, for most chromosomes positive correlations between the frequency of disordered segments of 30+ amino acids and both recombination rates and G + C content were observed. Conclusions - These analyses demonstrate that the presence of disordered segments among plant proteins is associated with the rates of genetic recombination of their encoding genes. Altogether, these findings suggest that high recombination rates, as well as chromosomal rearrangements, could induce disordered segments in proteins during evolution., This work was supported by grants from Ministerio de Economía y Competitividad (MAT2011-23861) and Gobierno de Aragón (DGA-GC B18 to I.Y. and DGA-GC A06 to B.C.-M.). All these grants were partially funded by the EU FEDER Program. We acknowledge support from CSIC Open Access Publication Support Initiative, through its Unit of Information Resources for Research (URICI), to help cover the Open Access fee.

SummaryDespite the great advances in microbial ecology and the explosion of high throughput sequencing, our ability to understand and integrate the global biogeochemical cycles is still limited. Here we propose a novel approach to summarize the complexity of the Sulfur cycle based on the minimum ecosystem concept, the microbial mat model and the relative entropy of protein domains involved in S-metabolism. This methodology produces a single value, called the Sulfur Score (SS), which informs about the specific S-related molecular machinery. After curating an inventory of microorganisms, pathways and genes taking part in this cycle, we benchmark the performance of the SS on a collection of 2,107 non-redundant RefSeq genomes, 900 metagenomes from MG-RAST and 35 metagenomes analyzed for the first time. We find that the SS is able to correctly classify microorganisms known to be involved in the S-cycle, yielding an Area Under the ROC Curve of 0.985. Moreover, when sorting environments the top-scoring metagenomes were hydrothermal vents, microbial mats and deep-sea sediments, among others. This methodology can be generalized to the analysis of other biogeochemical cycles or processes. Provided that an inventory of relevant pathways and microorganisms can be compiled, entropy-based scores could be used to detect environmental patterns and informative samples in multi-genomic scale.

16 Pags.- 4 Tabls.- 5 Figs.- Supplementary material foundable online. This Document is Protected by copyright and was first published by Frontiers. All rights reserved. it is reproduced with permission., The pan-genome of a species is defined as the union of all the genes and non-coding sequences found in all its individuals. However, constructing a pan-genome for plants with large genomes is daunting both in sequencing cost and the scale of the required computational analysis. A more affordable alternative is to focus on the genic repertoire by using transcriptomic data. Here, the software GET_HOMOLOGUES-EST was benchmarked with genomic and RNA-seq data of 19 Arabidopsis thaliana ecotypes and then applied to the analysis of transcripts from 16 Hordeum vulgare genotypes. The goal was to sample their pan-genomes and classify sequences as core, if detected in all accessions, or accessory, when absent in some of them. The resulting sequence clusters were used to simulate pan-genome growth, and to compile Average Nucleotide Identity matrices that summarize intra-species variation. Although transcripts were found to under-estimate pan-genome size by at least 10%, we concluded that clusters of expressed sequences can recapitulate phylogeny and reproduce two properties observed in A. thaliana gene models: accessory loci show lower expression and higher non-synonymous substitution rates than core genes. Finally, accessory sequences were observed to preferentially encode transposon components in both species, plus disease resistance genes in cultivated barleys, and a variety of protein domains from other families that appear frequently associated with presence/absence variation in the literature. These results demonstrate that pan-genome analyses are useful to explore germplasm diversity., This work was supported by DGA – Obra Social La Caixa (grant number GA-LC-059-2011), Spanish MINECO (AGL2013-48756-R and CSIC13-4E-2490) and CONACyTMéxico (grant 179133) and DGAPA-PAPIIT/UNAM IN211814. CC was funded by Spanish MINECO grant BES-2011-045905 linked to AGL2010-21929. BC-M was funded by Fundación ARAID. The work conducted by the U.S. Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported under Contract No. DE-AC02-05CH11231.

Specific protein-DNA interactions are central to a wide group of processes in the cell and have been studied both experimentally and computationally over the years. Despite the increasing collection of protein-DNA complexes, so far only a few studies have aimed at dissecting the structural characteristics of DNA binding among evolutionarily related proteins. Some questions that remain to be answered are: (a) what is the contribution of the different readout mechanisms in members of a given structural superfamily, (b) what is the degree of interface similarity among superfamily members and how this affects binding specificity, (c) how DNA-binding protein superfamilies distribute across taxa, and (d) is there a general or family-specific code for the recognition of DNA. We have recently developed a straightforward method to dissect the interface of protein-DNA complexes at the atomic level and here we apply it to study 175 proteins belonging to nine representative superfamilies. Our results indicate that evolutionarily unrelated DNA-binding domains broadly conserve specificity statistics, such as the ratio of indirect/direct readout and the frequency of atomic interactions, therefore supporting the existence of a set of recognition rules. It is also found that interface conservation follows trends that are superfamily-specific. Finally, this article identifies tendencies in the phylogenetic distribution of transcription factors, which might be related to the evolution of regulatory networks, and postulates that the modular nature of zinc finger proteins can explain its role in large genomes, as it allows for larger binding interfaces in a single protein molecule.

14 Pags.- 5 Figs. © Crop Science Society of America. This is an open access article distributed under the CC BY-NC-ND, Powdery mildew causes severe yield losses in barley production worldwide. Although many resistance genes have been described, only a few have already been cloned. A strong QTL (quantitative trait locus) conferring resistance to a wide array of powdery mildew isolates was identified in a Spanish barley landrace on the long arm of chromosome 7H. Previous studies narrowed down the QTL position, but were unable to identify candidate genes or physically locate the resistance. In this study, the exome of three recombinant lines from a high-resolution mapping population was sequenced and analyzed, narrowing the position of the resistance down to a single physical contig. Closer inspection of the region revealed a cluster of closely related NBSLRR (nucleotide-binding site–leucine-rich repeat containing protein) genes. Large differences were found between the resistant lines and the reference genome of cultivar Morex, in the form of PAV (presence-absence variation) in the composition of the NBS-LRR cluster. Finally, a template-guided assembly was performed and subsequent expression analysis revealed that one of the new assembled candidate genes is transcribed. In summary, the results suggest that NBS-LRR genes, absent from the reference and the susceptible genotypes, could be functional and responsible for the powdery mildew resistance. The procedure followed is an example of the use of NGS (next-generation sequencing) tools to tackle the challenges of gene cloning when the target gene is absent from the reference genome.

25 Pags.- 2 Tabls. The definitive version is available at: http://link.springer.com/journal/11032, The BARLEYMAP pipeline was designed to map both genomic sequences and transcripts against sequence-enriched genetic/physical frameworks, with plant breeders as the main target users. It reports the most probable genomic locations of queries after merging results from different resources so that diversity obtained from re-sequencing experiments can be exploited. In addition, the application lists surrounding annotated genes and markers, facilitating downstream analyses. Pre-computed marker datasets can also be created and browsed to facilitate searches and cross referencing. Performance is evaluated by mapping two sets of long transcripts and by locating the physical and genetic positions of four marker collections widely used for high-throughput genotyping of barley cultivars. In addition, genome positions retrieved by BARLEYMAP are compared to positions within a conventional genetic map for a population of recombinant inbred lines, yielding a gene-order accuracy of 96 %. These results reveal advantages and drawbacks of current in silico approaches for barley genomics. A web application to make use of barley data is available at http://floresta.eead.csic.es/barleymap. The pipeline can be set up for any species with similar sequence resources, for which a fully functional standalone version is available for download., This work was funded by DGA - Obra Social La Caixa [grant number GA-LC-059-2011] and by the Spanish Ministry of Science and Innovation [projects AGL2010-21929 and RTA2009-00006-C04-02]. Carlos P. Cantalapiedra is funded by [grant BES-2011-045905 linked to project AGL2010-21929]. Ridha Boudiar was supported by a Master’s fellowship from IAMZ-CIHEAM.

This chapter presents a practical overview and case study of the usage and capabilities of the primers4clades version 1.0 web server [Cont reras-Moreira et al., 2009], a software tool useful to desi gn degenerate PCR primers for gene-targeted analysis of metagenomic DNA (see also Chapter 28, Vol. I) and multilocus sequence analysis. Although direct shotgun sequencing of community DNA is now feasible [Venter et al., 2004], polymerase chain reaction (PCR) remains the most widely used technology to gain molecular markers for studies in molecular ecology and systematics.

Specific protein-DNA interactions are central to a wide group of processes in the cell and have been studied both experimentally and computationally over the years. Despite the increasing collection of protein-DNA complexes, so far only a few studies have aimed at dissecting the structural characteristics of DNA binding among evolutionarily related proteins. Some questions that remain to be answered are: (a) what is the contribution of the different readout mechanisms in members of a given structural superfamily, (b) what is the degree of interface similarity among superfamily members and how this affects binding specificity, (c) how DNA-binding protein superfamilies distribute across taxa, and (d) is there a general or family-specific code for the recognition of DNA. We have recently developed a straightforward method to dissect the interface of protein-DNA complexes at the atomic level and here we apply it to study 175 proteins belonging to nine representative superfamilies. Our results indicate that evolutionarily unrelated DNA-binding domains broadly conserve specificity statistics, such as the ratio of indirect/direct readout and the frequency of atomic interactions, therefore supporting the existence of a set of recognition rules. It is also found that interface conservation follows trends that are superfamily-specific. Finally, this article identifies tendencies in the phylogenetic distribution of transcription factors, which might be related to the evolution of regulatory networks, and postulates that the modular nature of zinc finger proteins can explain its role in large genomes, as it allows for larger binding interfaces in a single protein molecule.

19 Pag., 4 Tabl., 14 Fig., Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5′ RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of σ factors that control the expression of about 80% of these genes. As expected, the housekeeping σ70 was the most common type of promoter, followed by σ38. The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli., National Institutes of Health, grant GM071962-03. Department of Energy, grant GTLDE-FC02-02ER63446. Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico) grant 83686 G.I.

1 .pdf with the full text of article (13 Pags., 5 Figs.) + Supplemental data into 8 Additional Files (1 Fig., 7 Tabls.), The intrinsically unstructured state of some proteins, observed in all living organisms, is essential for basic cellular functions. In this field the available information from plants is limited but it has been reached a point where these proteins can be comprehensively classified on the basis of disorder, function and evolution.ResultsOur analysis of plant genomes confirms that nuclear-encoded proteins follow the same trend than other multi-cellular eukaryotes; however, chloroplast- and mitochondria- encoded proteins conserve the patterns of Archaea and Bacteria, in agreement with their phylogenetic origin. Based on current knowledge about gene transference from the chloroplast to the nucleus, we report a strong correlation between the rate of disorder of transferred and nuclear-encoded proteins, even for polypeptides that play functional roles back in the chloroplast. We further investigate this trend by reviewing the set of chloroplast ribosomal proteins, one of the most representative transferred gene clusters, finding that the ribosomal large subunit, assembled from a majority of nuclear-encoded proteins, is clearly more unstructured than the small one, which integrates mostly plastid-encoded proteins.ConclusionsOur observations suggest that the evolutionary dynamics of the plant nucleus adds disordered segments to genes alike, regardless of their origin, with the notable exception of proteins currently encoded in both genomes, probably due to functional constraints., This work was supported by grants from Ministerio de Economía y Competitividad (MAT2011-23861 to I.Y.) and Gobierno de Aragón (DGA-GC B18 to I.Y. and DGA-GC A06 to B.C-M). All these grants were partially financed by the EU FEDER Program.

Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite their importance, a lack of genomic information and resources has hindered the functional characterisation of genes in major crops. The recent release of high-quality reference sequences for these crops underpins a suite of genetic and genomic resources that support basic research and breeding. For wheat, these include gene model annotations, expression atlases and gene networks that provide information about putative function. Sequenced mutant populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources. This review provides a helpful guide for plant scientists, especially those expanding into crop research, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of crops of vital importance for food and nutrition security.

Ensembl Genomes (https://www.ensemblgenomes.org) provides access to non-vertebrate genomes and analysis complementing vertebrate resources developed by the Ensembl project (https://www.ensembl.org). The two resources collectively present genome annotation through a consistent set of interfaces spanning the tree of life presenting genome sequence, annotation, variation, transcriptomic data and comparative analysis. Here, we present our largest increase in plant, metazoan and fungal genomes since the project's inception creating one of the world's most comprehensive genomic resources and describe our efforts to reduce genome redundancy in our Bacteria portal. We detail our new efforts in gene annotation, our emerging support for pangenome analysis, our efforts to accelerate data dissemination through the Ensembl Rapid Release resource and our new AlphaFold visualization. Finally, we present details of our future plans including updates on our integration with Ensembl, and how we plan to improve our support for the microbial research community. Software and data are made available without restriction via our website, online tools platform and programmatic interfaces (available under an Apache 2.0 license). Data updates are synchronised with Ensembl's release cycle.